Aiguo Han

Aiguo Han is an Assistant Professor at the Department of Biomedical Engineering and Mechanics, College of Engineering, Virginia Tech. He holds affiliate appointments at Virginia Tech's Department of Mechanical Engineering and an adjunct position at UIUC's Department of Electrical and Computer Engineering. His research focuses on quantitative ultrasound imaging, machine learning applications in medical diagnostics, and transcranial ultrasound techniques for brain imaging and neuromodulation.

Education:

• Ph.D. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (2014)
• M.S. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (2011)
• B.S. in Acoustics, Nanjing University (2008)

Research Interests: Dr. Han develops advanced ultrasound methodologies for liver fat quantification, cancer diagnosis, preterm birth risk assessment, and neuroimaging. His work integrates machine learning to enhance diagnostic accuracy and employs computational modeling to understand ultrasonic wave propagation in biological tissues.

Publication Trends: Recent studies emphasize deep learning in ultrasound, quantitative biomarker development, and clinical translation of imaging technologies. Key subfields include liver steatosis assessment, transcranial ultrasound, and reproductive health monitoring.

Scientific Awards:

• NIH NIBIB Trailblazer Award (2022)
• Fellow, AIUM (2021)
• IEEE Distinguished Reviewer Awards
• Young Investigator Travel Grant, ASA (2018)
• AIUM New Investigator Award (2016)

Professional Service: Dr. Han serves on committees for AIUM, RSNA QIBA, and IEEE UFFC. He reviews for NIH and NSF grants and contributes to editorial boards including European Radiology's Ultrasound Section.

Lab: Leads the Biomedical Ultrasound Research Group (BURG), focusing on clinical ultrasound applications and computational modeling.